Specifying Abnormal Action Qualifications with Sensing in FLUX

Planning agents in real-world environments have to face the Qualification Problem, i.e., the failure of an action execution due to unexpected circumstances. Sensing actions are used to derive additional state knowledge. We present a high-level programming method to combine these two approaches in the agent programming language FLUX, which builds on the general action representation formalism of the Fluent Calculus. It is shown how this combination allows for an efficient reasoning about the causes of unexpected action failures. The explanations for an action failure help an agent to recover from unexpectedly failed plans.

[1]  Michael Thielscher,et al.  Inferring Implicit State Knowledge and Plans with Sensing Actions , 2001, KI/ÖGAI.

[2]  Mark Witkowski,et al.  High-Level Robot Control through Logic , 2000, ATAL.

[3]  Hudson Turner,et al.  Satisfiability planning with Causal Theories , 1998, KR.

[4]  Giuseppe De Giacomo,et al.  Execution Monitoring of High-Level Robot Programs , 1998, KR.

[5]  Hector J. Levesque,et al.  GOLOG: A Logic Programming Language for Dynamic Domains , 1997, J. Log. Program..

[6]  Franz Baader,et al.  KI 2001: Advances in Artificial Intelligence , 2001, Lecture Notes in Computer Science.

[7]  Michael Thielscher,et al.  Under Consideration for Publication in Theory and Practice of Logic Programming Flux: a Logic Programming Method for Reasoning Agents , 2003 .

[8]  Nicholas R. Jennings,et al.  Agent Theories, Architectures, and Languages: A Survey , 1995, ECAI Workshop on Agent Theories, Architectures, and Languages.

[9]  Gerhard Brewka,et al.  Adding Priorities and Specificity to Default Logic , 1994, JELIA.

[10]  J. Lloyd.  Foundations of Logic Programming , 1984, Symbolic Computation.

[11]  Patrick Doherty,et al.  TAL: Temporal Action Logics Language Specification and Tutorial , 1998, Electron. Trans. Artif. Intell..

[12]  John McCarthy,et al.  Epistemological Problems of Artificial Intelligence , 1987, IJCAI.

[13]  Frank Wolter,et al.  Semi-qualitative Reasoning about Distances: A Preliminary Report , 2000, JELIA.

[14]  Thom W. Frühwirth,et al.  Theory and Practice of Constraint Handling Rules , 1998, J. Log. Program..

[15]  Jan Jaspars,et al.  Logic in action , 1991 .

[16]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[17]  Michael Thielscher,et al.  The Qualification Problem: A solution to the problem of anomalous models , 2001, Artif. Intell..

[18]  Michael Thielscher,et al.  Addressing the Qualification Problem in FLUX , 2001, KI/ÖGAI.

[19]  Michael Thielscher,et al.  From Situation Calculus to Fluent Calculus: State Update Axioms as a Solution to the Inferential Frame Problem , 1999, Artif. Intell..